Mohamad Qadri

I am a PhD student at the Robotics Institute at Carnegie Mellon University, where I work with Michael Kaess in the Robotics Perception Lab. My research interests span robotics, computer vision, and machine learning, with a focus on developing new methods for perception, statistical inference, and decision-making in challenging real-world environments.

I completed my Masters in Robotics at CMU working with George Kantor on SLAM in agricultural environments. Previously, I worked with Simon Lucey and Laszlo Jeni on monocular 3D reconstruction. In my undergrad, I majored in Electrical Engineering at the University of Maryland - College Park.

Email  /  CV  /  Google Scholar  /  LinkedIn  /  Github

profile photo
Updates
[July '25]  Our paper Acoustic Neural 3D Reconstruction Under Pose Drift was accepted to IROS 2025.
[May '25]  I started a research internship at Meta Reality Labs in Redmond, WA.
[May '25]  Our paper Your Learned Constraint is Secretely a Backward Reachable Tube was accepted to the Reinforcement Learning Conference (RLC 2025).
[May '25]  I successfully passed my thesis proposal!
[Jul '24]  Our paper Z-Splat: Z-Axis Gaussian Splatting for Camera-Sonar Fusion was accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
[Apr '24]  Our paper "AONeuS: A Neural Rendering Framework for Acoustic-Optical Sensor Fusion" was accepted to SIGGRAPH 2024.
[Jan '24]  Our paper "Learning Covariances for Estimation with Constrained Bilevel Optimization" was accepted to ICRA 2024.
Research
Learning and Optimization
Your Learned Constraint is Secretly a Backward Reachable Tube
Mohamad Qadri, Gokul Swamy, Jonathan Francis, Michael Kaess, Andrea Bajcsy
RLC, 2025
arXiv
We prove that learned constraints, using Inverse Constraint Learning (ICL) algorithms, correspond to a dynamics-dependent Backward Reachable Tube (BRT) rather than a failure set.
Learning Covariances for Estimation with Constrained Bilevel Optimization
Mohamad Qadri, Zachary Manchester, Michael Kaess
ICRA, 2024
arXiv / video
We propose a gradient-based method for well-conditioned covariance estimation, as a bilevel optimization on factor graphs.
Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation
Mohamad Qadri, Michael Kaess
ICML (DAE Workshop), 2023
arXiv
We propose a method to learn observation models for state estimation even with non-differentiable optimizers.
InCOpt: Incremental Constrained Optimization Using the Bayes Tree
Mohamad Qadri, Paloma Sodhi, Joshua Mangelson, Frank Dellaert, Michael Kaess
IROS, 2022
paper / video / code
We present an Augmented Lagrangian-based incremental constrained optimizer that views matrix operations as message passing over the Bayes tree.
3D Reconstruction
Acoustic Neural 3D Reconstruction Under Pose Drift
Tianxiang Lin*, Mohamad Qadri*, Kevin Zhang, Adithya Pediredla, Christopher A. Metzler, Michael Kaess
IROS, 2025
arXiv
We tackle the challenge of accurate acoustic 3D reconstruction under drifting and noisy sensor pose by jointly optimizing the neural scene representation and sensor (sonar) poses. Our method enables high-fidelity reconstructions even under significant pose drift.
Z-Splat: Z-Axis Gaussian Splatting for Camera-Sonar Fusion
Ziyuan Qu, Omkar Vengurlekar, Mohamad Qadri, Kevin Zhang, Michael Kaess, Christopher Metzler, Suren Jayasuriya, Adithya Pediredla
TPAMI, 2024
arXiv
We extend Gaussian splatting to sonar cameras and propose fusion with RGB data for robust 3D reconstruction.
AONeuS: A Neural Rendering Framework for Acoustic-Optical Sensor Fusion
Mohamad Qadri*, Kevin Zhang*, Akshay Hinduja, Michael Kaess, Adithya Pediredla, Christopher Metzler
SIGGRAPH, 2024
arXiv
We fuse acoustic and optical measurements for high-resolution 3D surface reconstruction, even under limited baselines.
Neural Implicit Surface Reconstruction using Imaging Sonar
Mohamad Qadri, Michael Kaess, Ioannis Gkioulekas
ICRA, 2023
arXiv / video / code
Dense 3D reconstruction of objects using imaging sonar, with neural implicit functions.
Conditional GANs for Sonar Image Filtering with Applications to Underwater Occupancy Mapping
Tianxiang Lin, Akshay Hinduja, Mohamad Qadri, Michael Kaess
ICRA, 2023
arXiv / video
Application of cGANs to produce noise-free sonar images for improved underwater mapping.
Path Planning
Runahead A*: Speculative Parallelism for A* with Slow Expansions
Mohammad Bakhshalipour, Mohamad Qadri, Seyed Borna Ehsani, Dominic Guri, Maxim Likhachev, Phillip B. Gibbons
ICAPS, 2023
We introduce Runahead A*, a form of speculative parallelism for speeding up A* search in planning tasks.
RACOD: Algorithm/Hardware Co-Design for Mobile Robot Path Planning
Mohammad Bakhshalipour, Seyed Borna Ehsani, Mohamad Qadri, Dominic Guri, Maxim Likhachev, Phillip B. Gibbons
ISCA, 2022
paper
Joint algorithm/hardware co-design for path planning, with CODAcc hardware and the RASExp algorithm for parallel exploration.
Agricultural Robotics, Vision & Mapping
Autonomous Apple Fruitlet Sizing and Growth Rate Tracking using Computer Vision
Harry Freeman, Mohamad Qadri, Abhisesh Silwal, Paul O'Connor, Zachary Rubinstein, Daniel Cooley, George Kantor
Under Review
arXiv / video
Tracking and sizing apple fruitlets using deep learning and attentional graph neural networks across growth periods.
Toward Semantic Scene Understanding for Fine-Grained 3D Modeling of Plants
Mohamad Qadri, Harry Freeman, Eric Schneider, George Kantor
AIAFS AAAI, 2021
paper / video
Using semantics and environmental priors for accurate 3D mapping of agricultural environments.
Robotic Vision for 3D Modeling and Sizing in Agriculture
Mohamad Qadri
Masters thesis
paper
Other Projects
A Study of the Theoretical Foundations of Variational and Score Matching-based Diffusion Models
Ye Won Byun, Mohamad Qadri
pdf / code
Semi-Supervised Learning via Offline Pseudolabel Generation and Consistency Regularization
Mohamad Qadri, Maggie Collier
pdf / code
Exploring the link between Geodesically Convex Optimization and Contraction Analysis
Mohamad Qadri, Chiheb Boussemma
pdf
A Study of Joint-Space Control of Non-Linear Robotics Manipulators
Mohamad Qadri
pdf

Source code